521 karma · joined October 16, 2017
I'm not so sure. I suspect it'll follow the same roadmap as Gateway API, which it already kind of is with the Service Mesh Interface (https://smi-spec.io/)
I personally find that the service mesh value-prop is hard to justify for a serverless stack (mostly Cloud Run, but AWS Lambda too probably), and in situations where your services are mostly all in the same language and you can bake the features into libraries that are much easier to import.
Observability is a great example of this. In serverless-land, you're already getting the standard HTTP metrics (ex request count, response codes, latency, etc), tracing, and standard HTTP request logging "for free."
I think the biggest difference in price I saw was from my Z-Wave blinds versus Thread / Matter ones. However, the overwhelming majority of the cost for that is the blinds themselves so it's probably not the best comparison.
There's still a few sensors that there don't have a Matter equivalent yet, but I think that'll change soon.
It feels like you're coupling your application schema to your database schema, which is something you generally want to avoid.
Is this only for niches where you are ok with the db schema being tightly coupled? Do you use specific views to decouple the two schemas? In that scenario it seems like you might eventually get to a point where your view is more complicated than setting up a more traditional application.
So does a distributed database. A primary/replica has an ops burden too, and measuring that complexity is subjective.
With primary/replica you still take downtime during failover, you need to make sure you're testing the failover, upgrades aren't zero downtime in a lot of cases, etc.
You're essentially treating your database as a pet and a clustered option is much more cattle vs pet. This saves you time to develop other features (including working on reliability -- the most important feature)
I'd love to see this. I feel like I often default to adding context to my errors, which is probably better than defaulting to not wrapping at all, but would love to know what criteria you use to determine when adding context adds value
I want to be able to treat the servers in my database tier as cattle instead of pets and RDBMSs don't fit this paradigm well. Either NoSQL or NewSQL databases are, in my opinion, a much better place to start.
I feel like RDBMSs being the "default" option is because most people have worked with them in the past and already understand them. It doesn't mean they are the best tool for the job or even the tool most likely to solve the unknown problems you'll encounter in the future.
Even so, I plan on moving to HomeAssistant where I'll have to setup HTTPS and port-forwarding into my home network for integration with my voice assistant (Google Assistant). It seems like the future of SmartThings is questionable so I would rather migrate, especially with Matter as a standard looking to replace ZigBee and ZWave.
This doesn't really work like you'd expect and isn't recommended, as it only helps a particular use-case. The reason is that AWS Lambda will only keep a single instance of your function alive. That means if two requests come in at the same time, you'd see a cold start on one of those invocations.
Instead, you want to look at something like provisioned concurrency.
Google has Firestore as one of their approved databases for internal use.
Those are ones I have first hand experience with.
I know from friends that Microsoft runs things on Cosmos.
Netflix is pretty invested in Cassandra.
Seeing stuff like this makes me think they've taken almost no steps towards changing their culture that was heavily reported on a few years ago.
I tend to agree with the above point, but it has been quite some time since I watched it. I wonder if a new personal perspective and rapidly changing tech landscape would change how I feel about it today.
Disclaimer: I was previously employed by Amazon and currently Google. Opinions are my own, I'm not a lawyer, etc.
This is definitely one piece of Kubernetes that is getting a lot of attention recently. The three tools I've been paying attention to are Argo CD[0], Flux[1], and Config Sync[2].
All of these allow you to point your repository to a cluster and sync resources from the repo to the cluster, including deletes.
[0] https://argoproj.github.io/argo-cd/
[1] https://github.com/fluxcd/flux
[2] https://cloud.google.com/kubernetes-engine/docs/add-on/confi...
Disclaimer: I work at GCP, but not on the GKE team. Opinions are my own.
> Just remember ALL CAPS when you spell the man name
There are already comments here from users who presumably haven't read the article and are parroting this as fact.
Disclaimer: I work at AWS, however not for any service or marketing team. Opinions are my own.